tests Overview: Choose the Right Test Type

Every ABConvert test follows the same workflow—create, preview, launch, analyze, close. What changes is what you’re testing: prices, shipping rates, page templates, images, or checkout elements. This page explains what all tests have in common, then helps you navigate to the detailed guide for the test type you want to run.

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When to use it

• You are choosing a test type. Use the cards below to decide whether your change belongs in price, shipping, offer, URL redirect, template, theme, visual editor, checkout, or combined tests.
• You want the shared mental model. Read this page before the detailed guide if you are new to ABConvert.
• You need to understand the shared setup steps. Hypothesis, primary metric, test groups, audience targeting, preview, and analytics appear across test types.
• You are onboarding a teammate. Send them this overview before asking them to build a specific test.

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When NOT to use it

• You already know the exact test type. Go straight to that detailed guide.
• You need step-by-step setup screenshots. Each test-type page has its own setup walkthrough.
• You are debugging traffic assignment. Use Audience targeting.
• You are deciding whether results are significant. Use Statistical significance.

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What every test includes

Regardless of which test type you choose, every ABConvert test shares these core components:

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1. Hypothesis and primary metric

Before you launch, write a clear hypothesis: “Raising the price from 29 to 34 USD will increase revenue per visitor by 15%.” Then select your primary metric:

• Revenue per visitor — Total revenue divided by total visitors (best for price and offer tests)
• Conversion rate — Orders divided by visitors (best for checkout and template tests)
• Average order value — Total revenue divided by total orders (best for upsell and bundle tests)

ABConvert tracks all metrics regardless of which you choose as primary. The primary metric determines which variant ABConvert flags as the “winner” when you reach statistical significance. See Lifecycle for what each state means and how to preview a variant on your storefront before launch.

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2. Test groups and traffic allocation

Define how many variants you want to test and what percentage of traffic each group receives. Most tests start with:

• Control (50%) — Your current experience
• Variant (50%) — The change you’re testing

You can add multiple variants (Control, Variant A, Variant B, Variant C) and adjust traffic splits as needed (e.g., 25% each for four groups).

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3. Audience targeting

Control which visitors enter your test using filters:

• Country — Restrict tests to specific markets
• Device type — Desktop only, mobile only, or all devices
• UTM parameters — Target visitors from specific campaigns, sources, or mediums
• Visitor type — New visitors only, returning visitors only, or all

Visitors who don’t match your filters see the default experience and are not counted in test analytics. See Audience Targeting for detailed configuration instructions.

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4. Preview mode

Before launching, use Preview to verify the test displays correctly on your storefront. Preview applies the variant to your session only—real shoppers still see the original. Preview mode lets you:

• Walk through the buyer journey as if you were a customer
• Switch between variants to test each one
• Catch display issues, app conflicts, or tracking gaps before going live

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5. Statistical significance tracking

ABConvert calculates statistical significance for each variant automatically. The significance indicator shows whether the difference between variants is likely real or just random noise. Aim for:

• 100-200 conversions per variant minimum
• At least 2 weeks of data to account for day-of-week variation
• 95% confidence level before making a final decision

See Statistical Significance for a deep dive into how ABConvert calculates confidence and when to end a test.

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Detailed guides for each test type

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Common mistakes

• Choosing a test type by UI location instead of the business question. Start with what you are trying to learn, then pick the test type that changes that lever.
• Testing multiple unrelated ideas at once. Use a combined test only when the changes belong to one strategy.
• Skipping Preview test. Preview before launch even when the setup looks simple.
• Picking conversion rate as the primary metric by default. Choose the metric that matches the decision: profit, revenue per visitor, average order value, or conversion rate.

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Next steps